Bokus
Andrew Madson, Toby Mao, Iaroslav Zeigerman - Data Transformation: The Definitive Guide, Häftad

Häftad, Engelska, 2027

Data Transformation: The Definitive Guide

Designing Scalable and Efficient Data Pipelines to Power Analytics, Machine Learning, and AI

Av Andrew Madson, Toby Mao, Iaroslav Zeigerman

613 kr

Kommande

Beskrivning
Data Transformation: The Definitive Guide provides a rigorous and practical roadmap for designing scalable, efficient, and maintainable data pipelines. Written by leaders in the field, this book introduces foundational principles and modern practices that treat data transformation with the same discipline as software development—equal parts theory and hands-on implementation.With guidance on everything from building reproducible, testable workflows to deploying industrial-grade frameworks, the book equips data professionals with the knowledge to tackle real-world challenges in analytics, machine learning, and AI. Squarely focusing on reliability and scale, the authors deliver essential strategies for turning raw data into fresh, trustworthy insights.Structure transformation pipelines for maintainability and reproducibilityApply modern data development workflows, including CI/CD and versioningManage complexity through modular pipeline design and best practicesEvaluate tools and frameworks like SQLMesh and adopt them with confidenceTroubleshoot data quality issues with robust testing and observability techniquesAccelerate delivery of analytics and ML products with scalable transformation foundations
Produktinformation
  • Utgivningsdatum: 2027-04-30
  • Mått: 178 x 233 x undefined mm
  • Format: Häftad
  • Språk: Engelska
  • Antal sidor: 350
  • Förlag: O'Reilly Media
  • ISBN: 9798341661424
Utforska kategorier
Mer om författaren

Andrew Madson is an experienced data leader with 17 years of experience leading technical teams. Currently the Head of Evangelism and Education at Tobiko - the creators of SQLMesh and SQLGlot, Andrew has held senior leadership positions at institutions such as JP Morgan, LPL Financial, MassMutual, and Arizona State University. In addition to leading data teams, Andrew is a professor of data science and analytics at several universities, where he teaches graduate courses in machine learning, statistics, SQL, R, Python, Tableau, and Power BI. Toby Mao is the Co-Founder and CTO of Tobiko Data and creator of SQLMesh, a pioneering data transformation framework changing how organizations develop data pipelines. With deep experience at Netflix and Airbnb, he has implemented transformation solutions at a massive scale. His expertise in incremental loading methodologies and efficient pipeline architectures is complemented by his innovative work on SQLGlot, a SQL parser and transpiler enabling cross-platform transformations. Major organizations like Harness have adopted his methodologies, demonstrating their real-world impact. Iaroslav Zeigerman is the Co-founder and Chief Architect at Tobiko Data, with over a decade of experience in data, ML, and experimentation platforms. Previously, he led AI/ML data engineering at Apple and worked on Netflix's petabyte-scale data systems. He is a core contributor to SQLGlot and the creator of m2cgen, showcasing his innovation in data transformation. At Tobiko, he leads the development of SQLMesh, a modern DevOps-inspired data transformation framework. A frequent speaker at top data conferences, Iaroslav is recognized for his practical expertise in building reliable, large-scale data systems.

Betyg & recensioner

0 recensioner

Inga recensioner tillgängliga.

Mer från samma författare